Protein kinase A catalytic-α and catalytic-β proteins have non-redundant functions

Raghuram, Viswanathan; Salhadar, Karim; Limbutara, Kavee; Park, Eui‐Jung; Yang, Chin‐Rang; Knepper, Mark A.

doi:10.1101/2020.07.01.182691

Cited by 2 publications

(3 citation statements)

References 26 publications

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“…Their catalytic residues are conserved so it is likely that these isoforms are regulated differently. Selective depletion of C vs. Cβ in kidney supports the conclusions that C and Cβ are functionally nonredundant but nothing is known yet about the array of splice variants (Raghuram et al, 2020). Their expression is also highly tissue specific and will likely be much more relevant for disease.…”

Section: Pka C-subunits and The Combinatorial Expansion Of Exonmentioning

confidence: 65%

The Tails of Protein Kinase A

Taylor

Søberg

Kobori

et al. 2022

Molecular Pharmacology

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PKA is a holoenzyme consisting of a regulatory (R) subunit dimer and two catalytic (C) subunits. There are two major families of C-subunits, C and C, and four functionally nonredundant R-subunits (RI, RI, RII, RII). In addition to binding to and being regulated by the R-subunits, the C-subunits are regulated by two tails-regions that each wrap around the N-and C-lobes of the kinase core. While the Ct-Tail is classified as an intrinsically disordered region (IDR), the Nt-Tail is dominated by a strong helix that is flanked by short IDRs. In contrast to the Ct-Tail, which is a conserved and highly regulated feature of all AGC kinases, the Nt-Tail has evolved more recently and is highly variable in vertebrates. Surprisingly and in contrast to the kinase core and the Ct-Tail, the entire Nt-tail is not conserved in non-mammalian PKAs. In particular, in humans C actually represents a large family of C-subunits that are highly variable in their Nt-Tail and also expressed in a highly tissue-specific manner. While we know so much about the C1 subunit, we know almost nothing about these C isoforms where C2 is highly expressed in lymphocytes and C3 and C4 isoforms account for ~50% of PKA signaling in brain. Based on recent disease mutations, the C proteins appear to be functionally important and non-redundant with the C isoforms. Imaging in retina also supports non-redundant roles for C as well as isoform-specific localization to mitochondria. This represents a new frontier in PKA signaling.

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Section: Pka C-subunits and The Combinatorial Expansion Of Exonmentioning

confidence: 65%

The Tails of Protein Kinase A

Taylor

Søberg

Kobori

et al. 2022

Molecular Pharmacology

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“…We evaluate our approach on previously published phosphoproteomic data. This includes data sets from more than one hundred public repositories [4] and additionally validate these results on recently published data [26, 27, 28, 29, 30] and in case of cross-linking data we use previously published data to evaluate our transfer learning approach [31, 32, 33].…”

Section: Introductionmentioning

confidence: 62%

“…For validation we use five data sets [28, 29, 30, 26, 27]. For each data set, we used the original search results from MaxQuant alongside the raw spectra.…”

Section: Methodsmentioning

confidence: 99%

AHLF: ad hoc learning of peptide fragmentation from mass spectra enables an interpretable detection of phosphorylated and cross-linked peptides

Altenburg

Wang

Muth

et al. 2020

Preprint

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Motivation:Publicly available mass spectrometry-based proteomics data has grown exponentially in the recent past. Yet, large scale spectrum-centered analysis usually involves predefined fragmentation features that are limited and prone to be biased. Using deep learning, the decision making for a suitable fragmentation model can be carried out in a data-driven manner. Results: We introduce a framework that allows end-to-end training of generic deep learning models on a large collection of high resolution tandem mass spectra. In this case we used 19.2 million labeled spectra from more than a hundred individual PRIDE repositories. In our framework, we developed a representation that captures the complete information of a high-resolution spectrum facilitating a loss-less reduction of the number of features largely independent of the actual resolution. Additionally, it allows us to use common trainable layers, e.g. recurrent or convolutional operations. Specifically, we use a deep network of stacked dilated convolutions to model long range associations between any peaks within a tandem mass spectrum. We exemplify our approach by learning to detect post-translational modifications -in this case, protein phosphorylation -only based on a given mass spectrum in a fully data-driven manner. To the best of our knowledge, this is the first end-to-end trained deep learning model on tandem spectra that is able to ad hoc learn fragmentation patterns in high-resolution spectra. Our approach outperforms the current state-of-the-art in predicting if a mass spectrum originates from a phosphorylated peptide. Availability: Our deep learning framework is implemented in tensorflow. The open source code including trained weights is available at gitlab.com/dacs-hpi/ahlf Contact: bernhard.renard@hpi.de

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Protein kinase A catalytic-α and catalytic-β proteins have non-redundant functions

Cited by 2 publications

References 26 publications

The Tails of Protein Kinase A

The Tails of Protein Kinase A

AHLF: ad hoc learning of peptide fragmentation from mass spectra enables an interpretable detection of phosphorylated and cross-linked peptides

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